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Daubenmire Versus Line-Point Intercept: A Response to Thacker et al. (2015)

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Abstract

On the Ground: Thacker et al. compared two common techniques for assessing greater sage-grouse habitat: Daubenmire quadrats and line-point intercept sampling. Sampling only 16 Daubenmire quadrats may not have been adequate to support Thacker et al.'s assertion that line-point sampling yields higher cover values and that the two methods are not comparable. Using data from sagebrush ecosystems in Montana, we show that mean percent cover changes depending on the number of Daubenmire quadrats sampled and that 16 Daubenmire quadrats may not be sufficient to accurately characterize sagebrush vegetation. Assessing the appropriate sampling effort for the method and study is a crucial part of designing sampling protocols and has implications for greater sage-grouse management and conservation.

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... Among the various vegetation sampling techniques described in the scientific literature, visual assessment methods such as Daubenmire and other size quadrats, and line-point intercept (LPI) methods are often used to assess cover at the species or functional group level (Thacker et al. 2015). Several authors have compared the two methods, trying to identify the most efficient way to sample plant cover both in greenhouse experiments and natural ecosystems (Dethier et al. 1993;Floyd and Anderson 1987;Gregg 2006;Herrick et al. 2005;Hulvey et al. 2018;Karl et al. 2016;Martyn et al. 2015;Thacker et al. 2015). In these studies, the two methods were evaluated for rangeland habitat management and conservation, with an emphasis on greater sage-grouse [Centrocercus urophasianus (Bonaparte, 1827)] habitat monitoring (Hulvey et al. 2018;Karl et al. 2016;Martyn et al. 2015;Thacker et al. 2015). ...
... Several authors have compared the two methods, trying to identify the most efficient way to sample plant cover both in greenhouse experiments and natural ecosystems (Dethier et al. 1993;Floyd and Anderson 1987;Gregg 2006;Herrick et al. 2005;Hulvey et al. 2018;Karl et al. 2016;Martyn et al. 2015;Thacker et al. 2015). In these studies, the two methods were evaluated for rangeland habitat management and conservation, with an emphasis on greater sage-grouse [Centrocercus urophasianus (Bonaparte, 1827)] habitat monitoring (Hulvey et al. 2018;Karl et al. 2016;Martyn et al. 2015;Thacker et al. 2015). However, we have found no comparative studies focused on informing decisions around management of invasive annual grasses in rangelands. ...
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Scientists and natural resource managers require suitable vegetation survey methods to assess the success of rangeland restoration projects. Visual estimation and point intercept methods are commonly used to evaluate vegetation cover. This study compared the performance of one visual (quadrat-based) and two line point intercept (LPI – canopy and basal) methods to assess biodiversity, cover, and to estimate biomass production on sites invaded by introduced annual grasses across Wyoming, USA. Greater species richness and higher Shannon index values were measured in quadrats, while introduced annual and native perennial graminoid cover values were higher in LPI canopy in general. Overall, these outcomes indicate quadrats as the most suitable survey method when biodiversity monitoring is the primary objective, while suggesting LPI canopy when monitoring vegetation cover is prioritized. Finally, our regression models indicated quadrat-based estimates as the most reliable to predict introduced annual and native perennial graminoid biomass.
... To address our first objective, if 15 cores is sufficient for different sized fields, we quantified the relationship between sampling densities ranging from 0.74 (large fields) to 2.48 samples ha −1 (small fields) and the CV across samples made up of 15 randomly selected cores per field. We did this using a reverse-jackknife technique modified from Martyn et al. (2015). To start, we randomly selected two cores and calculated the CV for those two cores. ...
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On The Ground • Method comparison studies are necessary to reconcile monitoring methods that have arisen among disparate programs; however, we find that Thacker et al.’s study comparing Daubenmire frame (DF) and line-point intercept (LPI) methods for estimating vegetation cover is not adequate to support their conclusions. • Because the DF and LPI methods estimate different aspects of vegetation cover (total canopy vs. foliar cover), there should be no a priori expectation that the two techniques would produce the same results. • Thacker et al. omit critical information about their methods (sampling design, training and calibration, indicator calculations) that could have a large impact on their results and how they can be interpreted. • Differences in results between different vegetation cover measurement techniques can also be attributable to factors like observer training and calibration, plot heterogeneity and complexity, spatial distribution of vegetation, plant morphology, and plot size; thus it is difficult to draw strong conclusions from a single study. • Rather than implementing both DF and LPI techniques in sage-grouse studies as Thacker et al. recommend, effort should instead be invested in ensuring that sampling for one selected method is adequate. • Critical evaluations of vegetation measurement methods to advance the science of rangeland monitoring should be conducted and reported in a rigorous manner, provide a thorough review of previous studies, and discuss how new results contribute to existing knowledge.
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On the Ground Evaluation of range/habitat projects for sage-grouse require careful monitoring to measure their impact. Daubenmire canopy cover and line-point intercept did not yield similar results. As herbaceous canopy cover increased, the differences between the cover estimates increased. Adoption of both techniques by both groups may be the only feasible solution since institutional constraints limit either group from changing monitoring techniques.
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Accurate estimation of responses of understory plants to disturbance is essential for understanding the efficacy of management activities. However, the ability to assess changes in the abundance of plants may be hampered by inappropriate sampling methodologies. Conventional methods for sampling understory plants may be precise for common species but may fail to adequately characterize abundance of less common species. We tested conventional (modified Whittaker plots and Daubenmire and point-line intercept transects) and novel (strip adaptive cluster sampling [SACS]) approaches to sampling understory plants to determine their efficacy for quantifying abundance on control and thinned-and-burned treatment units in Pinus ponderosa forests in western Montana, USA. For species grouped by growth-form and for common species, all three conventional designs were capable of estimating cover with a 50% relative margin of error with reasonable sample sizes (3-36 replicates for growth-form groups; 8-14 replicates for common species); however, increasing precision to 25% relative margin of error required sample sizes that may be infeasible (11-143 replicates for growth-form groups; 28-54 replicates for common species). All three conventional designs required enormous sample sizes to estimate cover of nonnative species as a group (29-60 replicates) and of individual less common species (62-118 replicates), even with a 50% relative margin of error. SACS was the only design that efficiently sampled less common species, requiring only 6-11% as many replicates relative to conventional designs. Conventional designs may not be effective for estimating abundance of the majority of forest understory plants, which are typically patchily distributed with low abundance, or of newly establishing nonnative plants. Novel methods such as SACS should be considered in investigations when cover of these species is of concern.
Sage-grouse habitat assessment framework
  • E T Rinkes
  • And D E Naugle
STIVER, S.J., E.T. RINKES, AND D.E. NAUGLE. 2010. Sage-grouse habitat assessment framework. U.S. Bureau of Land Management.. Unpublished report. Boise, ID: Idaho State Office.
A canopy-coverage method of vegetation analysis
DAUBENMIRE, R.F. 1959. A canopy-coverage method of vegetation analysis. Northwest Science 33:43-66.